Triple
T12876045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yakima, Washington, United States |
E307967
|
entity |
| Predicate | distanceToSeattleInMiles |
P15605
|
FINISHED |
| Object | about 140 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: about 140 | Statement: [Yakima, Washington, United States, distanceToSeattleInMiles, about 140]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSeattleInMiles Context triple: [Yakima, Washington, United States, distanceToSeattleInMiles, about 140]
-
A.
distanceToSeattle
chosen
Indicates the measured or calculated distance between a given entity’s location and the city of Seattle.
-
B.
distanceFromTacoma (miles)
Indicates the physical distance, measured in miles, between an entity’s location and the city of Tacoma.
-
C.
distanceToOlympia
Indicates the measured spatial distance between a given location or object and Olympia.
-
D.
distanceToBellingham
Indicates the measured or estimated distance between a given entity’s location and the location of Bellingham.
-
E.
distanceToPortland
Indicates the measured distance between a given location and the city of Portland.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:38 p.m.